TTS
NeMo
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TTS | NeMo | |
---|---|---|
62 | 29 | |
8,806 | 10,084 | |
2.2% | 7.1% | |
0.0 | 9.8 | |
6 months ago | 2 days ago | |
Jupyter Notebook | Python | |
Mozilla Public License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TTS
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Any recommendation for human like voice AI model for conversation AI?
Fast or good, choose one
Mozilla's TTS is a python package installable with pip and uses cpu or gpu resources to render a choice of voices, they mostly sound natural and this is the good. https://github.com/mozilla/TTS
Mycroft's mimic3 is the default voice renderer for the Mycroft project that runs on pi hardware and sounds ok-ish, that is the fast. https://github.com/MycroftAI/mimic3
There are many others but these are the two I use according to if it needs to run on limited hardware or if the cycles fall freely from the sky.
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Coqui.ai Is Shutting Down
Coqui-ai was a commercial continuation of Mozilla TTS and STT (https://github.com/mozilla/TTS).
At the time (2018-ish), it was really impressive for on-device voice synthesis (with a quality approaching the Google and Azure cloud-based voice synthesis options) and open source, so a lot of people in the FOSS community were hoping it could be used for a privacy-respecting home assistant, Linux speech synthesis that doesn't suck, etc.
After Mozilla abandoned the project, Coqui continued development and had some really impressive one-shot voice cloning, but pivoted to marketing speech synthesis for game developers. They were probably having trouble monetizing it, and it doesn't surprise me that they shut down.
An equivalent project that's still in active development and doing really well is Piper TTS (https://github.com/rhasspy/piper).
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What self hosted app do you wish existed?
An RSS reader that integrates TTS (or TTS)
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Audio Converter! How to write one in c/c++?
My solution would be to use a speech synthesis library, maybe eSpeak or Festival, just for ease of use; I think they each provide a library that you could use from C or C++ easily. This one from Mozilla is a more modern system with better-quality output, but it looks like it's set up to run through Python, and I haven't looked at it closely enough to see how much work it would be to get it working for you.
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Web Speech API is (still) broken on Linux circa 2023
There is a lot of TTS and SST development going on (https://github.com/mozilla/TTS; https://github.com/mozilla/DeepSpeech; https://github.com/common-voice/common-voice). That is the only way they work: Contributions from the wild.
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[P] Balacoon: free-to-use text-to-speech
unfortunately not yet. I need to expand the library of languages and voices. looking around, it seems only Coqui had some traction re Brazilian Portuguese: https://github.com/mozilla/TTS/issues/160. If you foresee wide adoption of the tech for this locale, hit me up with DM
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Text to speech free
I haven't used it, but there's also mozilla/TTS.
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Does anyone know how to set up Mozilla TTS to work with firefox's reader view?
Mozilla TTS
- Conteúdo removido do rb que fiz sobre a destruição do Rio Doce 853KM de rio pela Vale e BHP Billings
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[D] Looking for someone to do a small coding job
Instead, just use Firefox's open-source TTS model: https://github.com/mozilla/TTS
NeMo
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[P] Making a TTS voice, HK-47 from Kotor using Tortoise (Ideally WaveRNN)
I don't test WaveRNN but from the ones that I know the best that is open source is FastPitch. And it's easy to use, here is the tutorial for voice cloning.
- [N] Huggingface/nvidia release open source GPT-2B trained on 1.1T tokens
- [D] What is the best open source text to speech model?
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[D] JAX vs PyTorch in 2023
Nowadays... bigger repos like https://github.com/NVIDIA/NeMo are all pytorch, lots of work also published by Meta and Microsoft is all torch. I check new work on GitHub all the time and I haven't seen a Tensorflow repo in years except one.
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[D] What's stopping you from working on speech and voice?
- https://github.com/NVIDIA/NeMo
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Can I use PyTorch to build a fast capitalization recoverer?
Can’t you use the NeMo model and just strip the punctuation from the output again if you don’t want it? You can also fine tune the the model with capitalization only if you look at the examples https://github.com/NVIDIA/NeMo/blob/stable/tutorials/nlp/Punctuation_and_Capitalization.ipynb The capitalization and punctuation are annotated separately (U indicates that the word should be upper cased, and O - no capitalization ). The model seems to be a token level classifier not seq to seq so there should also be a way to get just the capitalization part but you would have to look into the model as it’s not shown in the examples.
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I made a free transcription service powered by Whisper AI
I think there's been talk to do speaker diarization with whisper-asr-webservice[0] which is also written in python and should be able to make use of goodies such as pyannote-audio, py-webrtcvad, etc.
Whisper is great but at the point we get to kludging various things together it starts to make more sense to use something like Nvidia NeMo[1] which was built with all of this in mind and more
[0] - https://github.com/ahmetoner/whisper-asr-webservice
[1] - https://github.com/NVIDIA/NeMo
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Mozilla Common Voice - Korean Language is live - Help Build a Korean Corpus for Training AI/Navi/etc
[커먼보이스 전자우편](mailto:[email protected]) || Common Voice || Korean Language Homepage || FAQs || Speaking Aloud and Reviewing Recordings || Sentence Collector || NVidia/NeMo
- Whisper – open source speech recognition by OpenAI
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Using Edge Biometrics For Better AI Security System Development
The final security grain was added with speech-to-text anti-spoofing built on QuartzNet from the Nemo framework. This model provides a decent quality user experience and is suitable for real-time scenarios. To measure how close what the person says to what the system expects, requires calculation of the Levenshtein distance between them.
What are some alternatives?
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
TensorFlowTTS - :stuck_out_tongue_closed_eyes: TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, French, Korean, Chinese, German and Easy to adapt for other languages)
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
espnet - End-to-End Speech Processing Toolkit
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.